OneHotEncoding sample

docs/samples/Microsoft.ML.Samples/Dynamic/OneHotEncodingTransform.cs

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+using System;
+using System.Collections.Generic;
+using Microsoft.ML.Data;
+using static Microsoft.ML.Transforms.OneHotEncodingTransformer;
+
+namespace Microsoft.ML.Samples.Dynamic
+{
+    public static class OneHotEncodingTransform
+    {
+        public static void Example()
+        {
+            // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
+            // as well as the source of randomness.
+            var ml = new MLContext();
+
+            // Get a small dataset as an IEnumerable and convert it to an IDataView.
+            IEnumerable<SamplesUtils.DatasetUtils.SampleInfertData> data = SamplesUtils.DatasetUtils.GetInfertData();
+            var trainData = ml.Data.LoadFromEnumerable(data);
+
+            // Preview of the data.
+            //
+            // Age  Case  Education  Induced     Parity  PooledStratum  RowNum  ...
+            // 26   1       0-5yrs      1         6         3             1  ...
+            // 42   1       0-5yrs      1         1         1             2  ...
+            // 39   1       0-5yrs      2         6         4             3  ...
+            // 34   1       0-5yrs      2         4         2             4  ...
+            // 35   1       6-11yrs     1         3         32            5  ...
+
+            // A pipeline for one hot encoding the Education column.
+            var pipeline = ml.Transforms.Categorical.OneHotEncoding("EducationOneHotEncoded", "Education", OutputKind.Bag);
+            // Fit to data.
+            var transformer = pipeline.Fit(trainData);
+
+            // Get transformed data
+            var transformedData = transformer.Transform(trainData);
+
+            // Getting the data of the newly created column, so we can preview it.
+            var encodedColumn = transformedData.GetColumn<float[]>(ml, "EducationOneHotEncoded");
+
+            // A small printing utility.
+            Action<string, IEnumerable<float[]>> printHelper = (colName, column) =>
+            {
+                foreach (var row in column)
+                {
+                    for (var i = 0; i < row.Length; i++)
+                        Console.Write($"{row[i]} ");
+                    Console.WriteLine();
+                }
+            };
+
+            printHelper("Education", encodedColumn);
+
+            // data column obtained post-transformation.
+            // 1 0 0 0 ...
+            // 1 0 0 0 ... 
+            // 1 0 0 0 ...
+            // 1 0 0 0 ... 
+            // 0 1 0 0 ...
+            // ....
+        }
+    }
+}